EP3756963B1 - Ein verfahren und ein system zur steuerung eines fahrzeugs bei einem einsatz - Google Patents

Ein verfahren und ein system zur steuerung eines fahrzeugs bei einem einsatz

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Publication number
EP3756963B1
EP3756963B1 EP20181505.7A EP20181505A EP3756963B1 EP 3756963 B1 EP3756963 B1 EP 3756963B1 EP 20181505 A EP20181505 A EP 20181505A EP 3756963 B1 EP3756963 B1 EP 3756963B1
Authority
EP
European Patent Office
Prior art keywords
variable
optimal
vehicle
control
power
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
EP20181505.7A
Other languages
English (en)
French (fr)
Other versions
EP3756963A1 (de
Inventor
Johannes RITZMANN
Oscar CHINELLATO
Andreas CHRISTON
Mauro SALAZAR
Christopher Onder
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
FPT Motorenforschung AG
Original Assignee
FPT Motorenforschung AG
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Publication of EP3756963A1 publication Critical patent/EP3756963A1/de
Application granted granted Critical
Publication of EP3756963B1 publication Critical patent/EP3756963B1/de
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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W20/00—Control systems specially adapted for hybrid vehicles
    • B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
    • B60W20/11—Controlling the power contribution of each of the prime movers to meet required power demand using model predictive control [MPC] strategies, i.e. control methods based on models predicting performance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/02—Conjoint control of vehicle sub-units of different type or different function including control of driveline clutches
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/10—Conjoint control of vehicle sub-units of different type or different function including control of change-speed gearings
    • B60W10/11—Stepped gearings
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W20/00—Control systems specially adapted for hybrid vehicles
    • B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
    • B60W20/12—Controlling the power contribution of each of the prime movers to meet required power demand using control strategies taking into account route information
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0008—Feedback, closed loop systems or details of feedback error signal
    • B60W2050/001—Proportional integral [PI] controller
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0008—Feedback, closed loop systems or details of feedback error signal
    • B60W2050/0011—Proportional Integral Differential [PID] controller
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0013—Optimal controllers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0031—Mathematical model of the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0037—Mathematical models of vehicle sub-units
    • B60W2050/0039—Mathematical models of vehicle sub-units of the propulsion unit
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0037—Mathematical models of vehicle sub-units
    • B60W2050/0041—Mathematical models of vehicle sub-units of the drive line
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/02—Clutches
    • B60W2510/0208—Clutch engagement state, e.g. engaged or disengaged
    • B60W2510/0216—Clutch engagement rate
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/06—Combustion engines, Gas turbines
    • B60W2510/0666—Engine power
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/08—Electric propulsion units
    • B60W2510/085—Power
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/10—Change speed gearings
    • B60W2510/1005—Transmission ratio engaged
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/24—Energy storage means
    • B60W2510/242—Energy storage means for electrical energy
    • B60W2510/244—Charge state
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/15—Road slope, i.e. the inclination of a road segment in the longitudinal direction
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/20—Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/02—Clutches
    • B60W2710/021—Clutch engagement state
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/06—Combustion engines, Gas turbines
    • B60W2710/0677—Engine power
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/08—Electric propulsion units
    • B60W2710/086—Power
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/10—Change speed gearings
    • B60W2710/1005—Transmission ratio engaged
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/62—Hybrid vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84—Data processing systems or methods, management, administration

Definitions

  • the present invention concerns a method and a system for controlling a vehicle on a mission, in particular by means of optimal control inputs determined such as to minimize fuel consumption and/or pollutant emissions.
  • Some vehicles are known to enjoy high flexibility properties since capable of satisfying power supply needs through the serial and/or parallel exploitation of at least one first power source and at least one second power source.
  • the first power source delivers power from a first energy storage and cannot recuperate energy
  • the second power source delivers power from a second energy storage and can provide energy to the second power source.
  • the first energy storage is a fuel tank and the first power source uses fuel from the fuel tank to generate energy.
  • the first power source is an internal combustion engine, but also other sources may be considered, such as fuel cells operating on gaseous fuels.
  • the first power source does not rely on fuel, such as when the first energy storage is represented by an overhead line and the first power source is a power converter.
  • the second power source is usually an electric motor/generator and the second energy storage is a battery.
  • control systems which are adapted to manage optimally the split of the required power between the available power sources.
  • the control systems operate to minimize fuel consumption while fulfilling constraints on the level of charge of the battery.
  • mission is here used to identify the completion of travel of a vehicle along a predetermined path or track.
  • Such a priori information typically includes the required speed of the vehicles and the features of the tracks to be followed, such as road gradients, surface conditions and the like.
  • the known control systems In order to determine optimal inputs for controlling the power flows within the vehicles, the known control systems carry out optimization methods based on the construction and solution of an optimal control problem.
  • the cost to be minimized typically includes terms representing the overall consumed fuel.
  • WO2018158524A1 discloses a method to calculate an optimal triplet of values respectively relating to the power that the electric motor must provide, the power that the engine must provide, and the ratio to be engaged in the gearbox.
  • An aim of the present invention is to satisfy the above-mentioned need.
  • reference number 101 indicates a vehicle comprising a first power source or generator and a second power source or generator.
  • Vehicle 101 further comprises a first and a second energy storage respectively coupled to the first and the second power source and from which the latter draw energy for driving vehicle 101.
  • the first power source only dissipates energy from the first energy storage, whereas the second power source can provide energy to the second energy storage.
  • vehicle 101 is a hybrid electric vehicle or HEV where, more in particular, the second energy storage and the second power source respectively comprise a battery BY and an electric motor EM.
  • the first energy storage and the first power source respectively comprise a fuel tank (not shown) and an internal combustion engine ICE.
  • Electric motor EM and battery BY are coupled to each other, for instance by means of a DC/DC converter, such that electric motor EM is supplied by power taken from batter BY.
  • Vehicle 101 further comprises an axle provided with a pair of traction wheels WL and an automotive differential D, to which outputs traction wheels WL are coupled.
  • the axle further comprises a pair of friction brakes BK respectively coupled to traction wheels WL to apply braking torques thereon.
  • vehicle 101 comprises a torque split TS, which is coupled to both engine ICE and motor EM to receive respectively engine and motor power therefrom and supply accordingly the sum of the received powers in input to differential D.
  • torque split TS which is coupled to both engine ICE and motor EM to receive respectively engine and motor power therefrom and supply accordingly the sum of the received powers in input to differential D.
  • wheels WL may be driven by both engine ICE and motor EM in a parallel fashion.
  • vehicle 101 is a parallel-type HEV.
  • Vehicle 101 further comprises a clutch CL and a gearbox GB connecting engine ICE to torque split TS in a selective manner.
  • gearbox GB has a not-shown input shaft selectively drivable by engine ICE via clutch CL and a not-shown output shaft that is directly coupled to torque split TS.
  • gearbox GB introduces a plurality of gear ratios between engine ICE and torque split TS. In particular, six increasing gear ratios are considered.
  • vehicle 101 comprises a transmission, e.g. a gear reducer GR, that couples motor EM to torque split TS.
  • gear reducer GR introduces a fixed gear ratio between motor EM and torque split TS.
  • vehicle 101 comprises a control unit ECU, in particular an on-board computer, which is coupled to battery BY, motor EM, gearbox GB, clutch CL, internal combustion engine ICE, torque split TS, and specifically also to friction brakes BK.
  • ECU control unit
  • on-board computer which is coupled to battery BY, motor EM, gearbox GB, clutch CL, internal combustion engine ICE, torque split TS, and specifically also to friction brakes BK.
  • Control unit ECU is configured to receive and store a plurality of parameters regarding a given mission to be pursued by vehicle 101.
  • control unit ECU is configured to determine the power to be supplied by engine ICE and motor EM, as well as to choose gears for gearbox GB, corresponding to the respective gear ratios, in order to guarantee the mission completion, a minimized fuel consumption, and the satisfaction of one or more constraints.
  • control unit ECU stores constraints that are relative to the charge level of battery BY at the end of the mission and, possibly, to the respect of the physical limits of vehicle 101.
  • control unit ECU receives and stores the above parameters before the starting of the mission and as a function of a variable z, which is associated to the actual position of vehicle 101 after the start of the mission.
  • variable z may directly represent the actual position of vehicle 101 along the track.
  • variable z may be for instance defined by the elapsed time from the starting of the mission.
  • the elapsed time is, indeed, associated to the actual position of vehicle 101; the association holds in view of the length/shape of the track and the land speed of vehicle 101, since the latter are assumed known a-priori in view of the mission.
  • variable z can take values between a given interval [ z 0 z f ], where z 0 can be arbitrarily set to a null value and z f depends on the assumed features of the track to be followed, given the mission.
  • control unit ECU receives and stores two parameters ⁇ , v as a function of the variable z.
  • parameters ⁇ , v are indicative of the assumed grade of the track to be followed by vehicle 101 and of the assumed land speed that vehicle 101 should take along the same track.
  • parameters ⁇ , v are respectively defined by the above grade of the track and land speed.
  • Parameters ⁇ , v are used by control unit ECU to compute other parameters as a function of the variable z, which are useful for control unit ECU to determine the appropriate power supply for wheels WL, as it will become clearer in the following of the disclosure.
  • ⁇ fd , r w , ⁇ ts , F trac , T trac,ts represent respectively the transmission ratio of differential D, the radius of wheel WL, the angular rate at the output of torque split TS, the tangential traction force exerted by wheels WL onto the track, and the total traction torque outputted by torque split TS and inputted to differential D.
  • ⁇ fd , r w are constant values, which are stored by control unit ECU.
  • F trac is computed by control unit ECU as a function of the parameters ⁇ , v, thanks to a mathematical model stored within control unit ECU.
  • control unit ECU stores the following mathematical model of F trac :
  • F trac F d ⁇ ⁇ + F m a + F br
  • F d , F m , F br represents respectively the drag forces (e.g. aerodynamic drag, rolling resistance and uphill driving force) acting on vehicle 101, the inertia of vehicle 101, and the braking force of brakes BK.
  • Parameter a is the acceleration of vehicle 101 and is computed by control unit ECU as the derivative of parameter v .
  • control unit ECU is configured to control the amount of power to be directly supplied by motor EM and to control the selection of the gear for gearbox GB.
  • control unit ECU is configured to operate engagement and disengagement of clutch CL, such that selection of the gear is unnecessary when clutch CL is opened.
  • Control unit ECU performs managing of clutch CL and of gearbox GB by:
  • control unit ECU updates a single discrete variable i to control clutch CL and gearbox GB.
  • discrete variable i takes integer values, each being associated to a corresponding gear, e.g. 1, 2, 3, 4, 5, 6, or associated to the disengaged status of clutch CL, e.g. 0.
  • the first variable is indicative of an operation mode of vehicle 101.
  • the variable i equal to zero indicates that vehicle 101 operates in a fully electric mode.
  • the possibility of choosing the gears indirectly implies the adaptability of vehicle 101 to operate in accordance with different track conditions.
  • Control unit ECU manages also the supply of power to torque split TS by:
  • control unit ECU updates a single continuous variable u to control the power supply from motor EM and from engine ICE.
  • T m,ts represents the torque provided by motor EM at torque split TS
  • T trac,ts represents the total traction torque outputted by torque split TS and inputted to differential D.
  • T e , ts 1 ⁇ u T trac , ts .
  • T e,ts represents the torque provided by engine ICE at torque split TS.
  • variable u is indicative of the instantaneous power P m provided by motor EM since the same P m is proportional to the product T m,ts ⁇ ⁇ ts and since T trac,ts , ⁇ ts are respectively derivable through equations 2, 3, by knowing parameters ⁇ , v.
  • control unit ECU can evaluate T m,ts from equation 4 and then P m by multiplying the product T m,ts ⁇ ⁇ ts by a known proportionality constant, which is stored in control unit ECU and is substantially defined by the product of the respective efficiencies of gear reducer GR and torque split TS.
  • Control unit ECU updates the first and the second variable by solving an optimal control problem.
  • the optimal control problem comprises the determination of values of the first and the second variable, as a function of variable z, which lead to the minimization of a chosen cost function.
  • variable z is the independent variable of the optimal control problem solved by control unit ECU.
  • the cost function is determined for at least a portion of the mission and is representative of a first quantity indicative of an energy consumed by the first power source after the portion itself is completed.
  • the first quantity is indicative of the fuel consumed by vehicle 101.
  • the cost function is a convex function in at least the first variable and a third variable, which is related to the second variable. All constraints are expressible in mathematical terms as equations or inequations comprising explicit functions of at least one of the first and the third variable. Each of the constraints defines a convex set of admissible values for at least one of the first variable, the third variable, and the state variable.
  • control unit ECU results in a convex optimization problem.
  • constraints comprise at least one first inequality constraint.
  • a first inequality constraint is expressible by an inequation, which has a first and a second member.
  • the first member is the total derivative of at least one state variable with respect to variable z , whereas the second member comprises terms that, in particular, are explicitly independent of the same state variable.
  • the state variable is indicative of the energy amount available to the second power source, such that the latter can generate power for driving vehicle 101. More precisely, the energy amount is stored within the battery BY and defines the state of charge of the battery BY. Specifically, the state variable is indicative of the state of charge of the battery BY.
  • the aforementioned first quantity is explicitly independent of the state variable
  • the constraints further comprise at least one first equality constraint reflecting a mathematical model of vehicle 101, for instance comprising the mathematical model of F trac in equation 1.
  • a first equality constraint comprises a third and a fourth member respectively comprising, in turn, convex functions in at least one of the first and the third variable.
  • Control unit ECU solves the optimal control problem in view of such a principle.
  • P m,ts defines the third variable and represents the power supplied by motor EM at torque split TS, namely the product T m,ts ⁇ ts .
  • P f , P trac,ts , E b , and P b represents respectively the fuel power, the traction power of wheels WL, the energy stored in battery BY, and the electric power supplied by battery BY.
  • P f is associated to a second quantity, which is indicative of an instantaneous power for driving the vehicle 101 and is a function of parameters ⁇ , v, variable i , and variable P .
  • the power supplied by battery BY includes inner resistive losses in the same battery BY.
  • Equations 14a, 14b and 14c express respectively the cost function, the first equality constraint and the first inequality constraint.
  • P b defines the second member of the first inequality constraint and the above first quantity is a function of P f ; as evident, P b and P f have no explicit dependency on E b , which defines the state variable.
  • Angular rate ⁇ e is proportional to ⁇ ts and the related proportionality constant is variable as a function of the selected gear of gearbox GB, i.e. of the value assumed by the discrete variable i. More precisely, ⁇ ts is equal to ⁇ e multiplied by the gear ratio that is associated to the value of variable i and by the efficiencies of clutch CL and gearbox GB.
  • Control unit ECU stores three mappings respectively relating the values of ⁇ 0, ⁇ 1 , ⁇ 2 to values of ⁇ e or ⁇ ts . Those mappings depend on the engine ICE and their derivation is performed experimentally, in particular by fitting experimental data with second order polynomials.
  • Vehicle 101 comprises a transducer H1 that is coupled to engine ICE and to control unit ECU; transducer H1 detects another quantity indicative of angular rate ⁇ e and generate a signal that is relative to such another quantity and received by control unit ECU for the extraction of actual values of the angular rate w e .
  • ⁇ m is proportional to ⁇ ts and is specifically obtainable through dividing ⁇ ts by the gear ratio of gear reducer GR and by the efficiency thereof.
  • ⁇ is further dependent by the sign of P m,ts , which may be also negative if the motor EM operates as a generator.
  • ⁇ is represented as a discontinuous function of P m,ts taking values ⁇ 1 when P m,ts is greater or equal to zero and values ⁇ 2 otherwise.
  • Control unit ECU stores three mappings respectively relating the values of ⁇ , ⁇ 1 , ⁇ 2 to values of ⁇ m or ⁇ ts . Those mappings depend on the motor EM and their derivation is performed experimentally, in particular by fitting experimental data with second order polynomials.
  • Vehicle 101 comprises a transducer H2 that is coupled to motor EM and to control unit ECU; transducer H2 detects a further quantity indicative of angular rate ⁇ m and generate a signal that is relative to such further quantity and received by control unit ECU for the extraction of actual values of the angular rate ⁇ m .
  • constraints of the optimal control problem further comprise second inequality constraints that set the feasible values of variables P m,ts and i, such that the physical limits of vehicle 101 are not violated.
  • the following expresses the other second inequality constraints: ⁇ e ⁇ ⁇ e , min , ⁇ e , max P e , ts ⁇ 0 , P e , ts , max ⁇ e ⁇ m ⁇ 0 , ⁇ m , max P m , ts ⁇ P m , ts , min ⁇ m , P m , ts , max ⁇ m E b ⁇ E b , min , E b , max
  • constraints comprise a third inequality constraint, which is specifically expressed as follows: E b z fin ⁇ E b 0
  • the third inequality constraint imposes that the level of charge or available energy of battery BY at the end of the mission cannot be inferior to that at the beginning of the mission.
  • the indicator function ⁇ is in the variables P m,ts , i, and E b since each of the parameters ⁇ e , P e,ts , ⁇ m , P m , and E b depends on one or more of the same variables P m,ts , i, and E b .
  • P m,ts and P trac,ts are simply renamed to P and P req for the sake of conciseness.
  • the Hamiltonian H is also discontinuous, i.e. non-smooth.
  • N ⁇ b E b ⁇ indicates the so-called normal cone, of which a more detailed description is given in the article " Time-optimal control policy for a hybrid electric race car", IEEE Transactions on Control System Technology, vol 25, no. 6, pp. 1921-1934, 2017 by M. Salazar et al.
  • Equation 30 implies that the derivative of the optimal costate is null when the state of charge of battery BY is neither at its lower nor its upper bound, whereas it is undetermined when the limits on the state of charge of battery BY are reached.
  • the optimal costate ⁇ is specifically a piecewise constant function with discontinuities in correspondence of values of z for which the limits on the state of charge of battery BY are reached.
  • Equation 31 implies that the value of the costate ⁇ at the end of the mission is inferior or equal to zero.
  • the costate ⁇ is conveniently replaced in equation 28 by a positive equivalence factor s being the negative of the costate ⁇ (i.e. equal to - ⁇ ).
  • the equivalence factor s has the physical meaning of a penalizing factor, which penalizes the usage of power from battery BY with respect to the usage of fuel power to move vehicle 101.
  • the optimal i* is determined by control unit ECU, by simply repeating the evaluation of P*, according to equation 37, and the evaluation of the cost function for each possible value of the discrete variable i. In such a manner, the couple of i*, P* leading to the lowest value of the cost function is regarded as the global optimum of the convex optimal control problem, provided that the optimal s* has been already determined.
  • control unit ECU determines the optimal s* by solving at least one boundary value problem, where specifically:
  • control unit ECU solves the boundary value problem by means of a shooting method, in particular a single shooting.
  • control unit ECU evaluates P and i according to the solution of the optimal control problem and an equivalence factor s s to determine a resulting E b .
  • a difference function between the resulting E b at the end of the mission and the corresponding target E b is determined.
  • control unit ECU determines the root of the difference function, e.g. by means of the well-known bisection method or Newton's method, such that s s is determined and thus the optimal s* is determined accordingly.
  • control unit ECU solves the boundary value problem for the whole mission, neglecting the constraints related to the state variable in the optimal control problem.
  • control unit ECU identifies the value z V of z for which the largest violation of the constraints related to the state variable occurs.
  • control unit ECU identifies the violation of the bounds defined by equation 14h.
  • the boundary value problem is split into two boundary value problems respectively related to a previous portion of the mission, corresponding to the interval from z 0 to z V , and to a next portion of the mission, corresponding to the interval from z V to z fin .
  • the target E b for the previous portion and the initial E b for the next portion are set to the corresponding violated bound.
  • Such an iterative approach is here referred to as a multi-point boundary value problem to distinguish the latter from a two-point boundary value problem, which is solved by control unit ECU at the first iteration.
  • the complete determination of the optimal piecewise constant s* allows the control unit ECU to determine, by definitively solving the optimal control problem, the optimal first and third variable, as well as the resulting optimal state variable, namely P*, i*, E b ⁇ , in particular.
  • control unit ECU forces the computed optimal P* to take a null value, although such computed P* is negative, when the optimal state variable reaches a value indicative that the maximum state of charge of the battery BY has been reached. Indeed, in such a case, battery BY cannot be recharged and motor EM should not work as a generator.
  • control unit ECU activates friction brakes BK to brake vehicle 101, instead of commanding regenerative braking through motor EM.
  • the amount of time in which P* is forced coincides with the time until the state of charge of battery BY approaches a predetermined tolerance inferior to the maximum level of charge.
  • control unit ECU restore the optimal P* to recuperate the requested negative power as fast as possible, unless the optimal values are so negative that the maximum level of charge of battery BY is newly overcome.
  • control unit ECU forces the optimal P* to take the minimum negative value leading to the reaching of the maximum level of charge of battery BY. Then, again, the optimal P* is forced to take a null value until the tolerance is approached.
  • the optimal state variable evaluated by control unit ECU corresponds to an optimal trajectory for a third quantity indicative of the state of charge of battery BY.
  • ⁇ ⁇ E b ⁇ / E b , max
  • the symbol ⁇ is used to indicate a variable representing the adimensional state of charge of battery BY, possibly expressible in percentage.
  • the optimal ⁇ * as a function of the variable z, defines the above optimal trajectory.
  • Control unit ECU implements the method outlined in Figure 2 , which is essentially based on the solution of the optimal control problem, in particular as already disclosed in detail, in order to control vehicle 101 during the mission.
  • Control unit ECU comprises a first logic block RTG or a reference trajectory generator, which outputs the optimal trajectory ⁇ * starting from parameters ⁇ , v as inputs.
  • the first logic block RTG solves the optimal control problem for the whole mission, specifically the problem stated in equations 27a, 27b, 27c in the manner disclosed above in detail.
  • the first logic block RTG solves the aforementioned multi-point boundary value problem to evaluate the optimal s*.
  • the first logic block RTG evaluate the optimal P*, i*, E b ⁇ according to the above disclosure or, more precisely, according to the Pontryagin's minimum principle, the non-smooth Hamiltonian H of equation 28, and the mathematical model of vehicle 101 of equations 1, 11, 12.
  • the first logic block RTG computes the optimal trajectory ⁇ * according to equation 39 and outputs the optimal trajectory ⁇ * itself as a reference trajectory.
  • the operation of the first logic block RTG is only based on a-priori information about the mission to be pursued by vehicle 101. Indeed, the only required inputs are the a-priori known parameters ⁇ , v stored by control unit ECU.
  • the first block RTG can also compute the optimal torque split ratio u* according to equation 38 and, accordingly, output the same optimal torque split ratio u* and the optimal discrete variable i *.
  • the outputted u* and i* are used by control unit ECU to control motor EM and engine ICE on one hand and clutch CL and gearbox GB on the other hand.
  • vehicle 101 would be open-loop controlled.
  • vehicle 101 further comprises a transducer device T1 coupled to battery BY and to control unit ECU.
  • Transducer device T1 is configured to detect actual values of the third quantity indicative of the state of charge of battery BY and to generate a signal related to the detected values.
  • Control unit ECU receives the signal generated by transducer device T1 and extracts from the signal, for each value of the variable z, a corresponding actual value ⁇ act associated to the actual state of charge of battery BY.
  • Control unit ECU additionally comprises a second logic block MPC or a model predictive controller, which receives the actual value ⁇ act , the parameters ⁇ , v, and the reference trajectory ⁇ * as inputs so as to output an updated reference trajectory ⁇ + and, conveniently, an updated optimal equivalence factor s + .
  • the superscript + has a similar meaning to that of the superscript* and refers to variables updated by the second logic block MPC. All the above-disclosed equations apply also to updated variables by trivially replacing the superscripts when appropriate. In the following, the recalling of a disclosed equation, in association to updated variables, implies the replacement of the superscripts.
  • the second logic block MPC repeatedly solves the optimal control problem for a moving interval of the variable z.
  • the moving interval starts with the actual value of z, corresponding to the actual value ⁇ act , and has a given size inferior than that of the entire interval related to the whole mission.
  • the second logic block MPC repeatedly solves a problem that differs from that stated in equation 27a, 27b, 27c for the interval of z or prediction horizon.
  • the problem solved by the second logic block MPC differs from that stated in equation 27a, 27b, 27c in the initial value set for the state variable E b , which corresponds to the actual value ⁇ act according to equation 39.
  • the size of the prediction horizon should be chosen in order to allow effective control of vehicle 101. Indeed, the greater is the size of the prediction horizon, the longer is the computational time for the second logic block MPC to update the outputs.
  • the minimum selectable size of the prediction horizon should be the maximal driving distance that the vehicle 101 can achieve during the updating time.
  • the second logic block MPC may solve the two-point boundary value problem, instead of the multi-point boundary value problem, or the latter as well.
  • the second logic block MPC evaluate also updated variables P + , i + , E b + according to the above disclosure or, more specifically, according to the Pontryagin's minimum principle, the non-smooth Hamiltonian H of equation 28, and the mathematical model of vehicle 101 of equations 1, 11, 12.
  • the second logic block MPC computes the updated trajectory ⁇ + according to equation 39 and outputs the updated trajectory ⁇ + itself, possibly together with the updated s + .
  • the second logic block MPC computes also an updated torque split ratio u + according to equation 38 and an updated discrete variable i + , which may possibly be outputted and used in replacement of the optimal torque split ratio u* and the optimal discrete variable i *, according to a not-shown embodiment.
  • the outputted u + and i + are used by control unit ECU to control motor EM and engine ICE on one hand and clutch CL and gearbox GB on the other hand.
  • vehicle 101 would be closed-loop controlled.
  • vehicle 101 further comprises another transducer device T2 coupled to control unit ECU and configured to detect a fourth quantity indicative of the total power required at torque split TS and to generate a signal related to the latter fourth quantity.
  • transducer device T2 is coupled to an accelerator (not shown) of vehicle 101; alternatively, transducer device T2 is coupled to the torque split TS.
  • Control unit ECU receives the signal generated by transducer device T2 and extracts from the signal, for each value of the variable z, a corresponding actual value P req,act associated to the actual total power required at torque split TS.
  • Control unit ECU additionally comprises:
  • the fourth logic block OCL uses the input s c and P req,act as the equivalence factor s and the required power, respectively, to solve the optimal control problem.
  • the fourth logic block OCL solves the optimal control problem on the basis of equations 34 and 37, evaluated for any possible value of the variable i, the cost function in equation 27a, and the mathematical model of vehicle 101 of equations 1, 11, 12.
  • the results of the solution are the optimal controls i c , u c , which are used by control unit ECU as the optimal updated first and second variable to control motor EM and engine ICE on one hand and clutch CL and gearbox GB on the other hand.
  • the above control unit ECU and the transducer devices T1, T2 make part of a system for controlling vehicle 101.
  • the logic blocks RTG, MPC, OCL define a multilayered control structure.
  • the disclosed method is computationally inexpensive, especially in respect to known methods, and the disclosed system can implement the disclosed method in a real-time fashion.
  • control accuracy is at least comparable to that of the known method, although the implementation is significantly faster.
  • the disclosed multilayered control structure allows the mixing of a-priori known information with real-time information for an optimal control of the vehicle 101 with an improved effectiveness, with respect to the known methods.
  • the properties of the chosen parameters and variables for modeling vehicle 101 allows the optimal control problem to be well-posed and solvable in a simple and time efficient manner.
  • the disclosed method and system allows, moreover, to control not only the power split between motor EM and engine ICE, but also the engagement/disengagement of clutch CL and the gear shift through gearbox GB.
  • the numeral adjectives are purely conventional; in particular, the third and the second variable may coincide each other.
  • the optimal power P* may be directly used to control vehicle 101.
  • Electric motor EM and internal combustion engine ICE are examples of the first and the second power source of vehicle 101. Therefore, electric motor EM and internal combustion engine ICE may be more generally replaced by the first and the second power source with appropriate straightforward adaptations.
  • the internal combustion engine ICE or the electric motor EM may be replaced by a converter configured to draw energy from an overhead line.
  • the parameters, quantities and variables related to engine ICE and the related fuel tank or the parameters, quantities and variables related to motor EM and battery BY have to be replaced with corresponding parameters, quantities and variables related to the converter and the overhead line.
  • the internal combustion engine ICE may be replaced by a fuel cell running on gaseous fuel or other kinds of fuel power source.
  • the third inequality constraint in equation 14i may be different; for instance, such a third inequality constraint may be replaced by a similar equality constraint.
  • the gear reducer GR may also introduce a plurality of gear ratios; in that case, the presence of further gear ratios may be taken into account by the possible values of the variable i.
  • Brakes BK may be only emergency brakes and remain always inactive during normal operation of vehicle 101; in such a case the mathematical models of vehicle 101 have to be revised accordingly.
  • control scheme shown in Figure 2 may be changed; in particular, the feedforwarding of the updated s + may be omitted or replaced by the direct feedforwarding of the optimal s* outputted by the first logic block RTG. Similarly, the feedback control loop may be closed directly on the reference trajectory ⁇ * outputted by the first logic block RTG. Furthermore, any other control law can be considered instead of a PI or a PID control law.
  • the dependency of the derivative of the state variable with respect to the state variable itself can also be considered.
  • the costate ⁇ is no longer constant or piecewise constant, but evolves according to an updated equation 30.
  • the multi-point boundary value problem can still be solved using single shooting, by determining the initial value of ⁇ or s for each portion rather than a constant value.
  • equation 14i could be rewritten to aim for a predetermined state of charge of battery BY differing from the initial one. This is especially promising for plug-in hybrid vehicles, where it is desirable to deplete the battery BY over a mission, as it can be recharged using power from an electricity grid at the destination.
  • the optimal control problem may involve only one constraint forming a set of constraints with just one element.

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Claims (19)

  1. Verfahren zum Steuern eines Fahrzeugs (101) auf einer Mission, wobei das Fahrzeug (101) eine erste und eine zweite Energiequelle (ICE, EM) zum Antreiben des Fahrzeugs (101) selbst umfasst,
    wobei das Verfahren die folgenden Schritte umfasst:
    • Lösen eines Problems einer optimalen Steuerung auf der Grundlage eines mathematischen Modells des Fahrzeugs (101), wobei das Problem einer optimalen Steuerung mindestens eine Zustandsvariable (Eb ) einbezieht,
    wobei das Lösen das Minimieren einer Kostenfunktion in Bezug auf eine erste und eine zweite Steuervariable (i, P) und unter Berücksichtigung einer Gruppe von Randbedingungen auf der Grundlage des Pontryagin-Minimalprinzips und auf der Grundlage der Minimierung einer Hamilton-Funktion (H), die dem Problem einer optimalen Steuerung zugeordnet ist, in Bezug auf die erste Steuervariable (i), die zweite Steuervariable (P) und eine Kostenvariable (λ), die konstant oder stückweise konstant mit Unstetigkeiten bei einem Maximalwert und einem Minimalwert für die Zustandsvariable ist, enthält; und
    • Steuern des Fahrzeugs (101) auf der Grundlage der Lösung des Problems einer optimalen Steuerung,
    wobei die Zustandsvariable (Eb ) einen Energiebetrag angibt, der für die zweite Energiequelle für die Erzeugung von Energie zum Antreiben des Fahrzeugs (101) verfügbar ist, die erste Steuervariable (i) eine diskrete Variable ist, die einen Betriebszustand des Fahrzeugs (101) angibt, und die zweite Steuervariable (P) eine kontinuierliche Variable ist, die eine Leistung (P) angibt, die durch die erste und/oder die zweite Energiequelle (ICE, EM) zugeführt wird;
    und wobei die Kostenfunktion zumindest für einen Abschnitt der Mission bestimmt wird, in Bezug auf die erste und die zweite Steuervariable (i, P) konvex ist und eine erste Größe darstellt, die eine Energie angibt, die durch die erste Energiequelle (ICE) verbraucht worden ist, nachdem der Abschnitt der Mission abgeschlossen worden ist;
    wobei die Gruppe von Randbedingungen mindestens eine Endpunktrandbedingung auf den zulässigen Werten, die die Zustandsvariable (Eb ) am Ende des Abschnitts der Mission annehmen kann, umfasst,
    wobei jede Randbedingung der Gruppe von Randbedingungen eine jeweilige konvexe Gruppe von zulässigen Werten für die erste Steuervariable (i) und/oder die zweite Steuervariable (P) und/oder die Zustandsvariable (Eb ) definiert,
    dadurch gekennzeichnet, dass es ferner die folgenden Schritte umfasst:
    • Bestimmen einer optimalen Zustandsvariablen (Eb *) in Übereinstimmung mit der Lösung des Problems einer optimalen Steuerung;
    • Erzeugen einer Referenzübertragungslinie (ξ*) für eine dritte Größe (ξ) bezüglich der Zustandsvariable (Eb ), insbesondere eines Ladungszustands einer Batterie (BY), die zum Versorgen derselben zweiten Energiequelle mit der zweiten Energiequelle gekoppelt ist, auf der Grundlage der bestimmten optimalen Zustandsvariable (Eb * );
    • Lösen eines weiteren Problems einer optimalen Steuerung auf der Grundlage des mathematischen Modells und unter Einbeziehung der Zustandsvariable (Eb ) und der ersten und der zweiten Steuervariable (i, P) als Optimierungsvariablen;
    • Erfassen eines tatsächlichen Wertes (ξact ) der dritten Größe (ξ);
    • Aktualisieren der optimalen Zustandsvariable (Eb * ) in Übereinstimmung mit der Lösung des weiteren Problems einer optimalen Steuerung; und
    • Aktualisieren der Referenzübertragungslinie (ξ*) auf der Grundlage der aktualisierten optimalen Zustandsvariable (Eb * );
    wobei das weitere Problem einer optimalen Steuerung die Minimierung einer weiteren Kostenfunktion in Bezug auf die erste und die zweite Steuervariable (i, P) unter Berücksichtigung der Gruppe von Randbedingungen und einer weiteren Randbedingung, die auferlegt, dass der Anfangswert der Zustandsvariable (Eb ) dem tatsächlichen Wert entspricht, umfasst;
    wobei die weitere Kostenfunktion für einen verkleinerten Abschnitt des Abschnitts der Mission bestimmt wird, in Bezug auf die erste und die zweite Steuervariable (i, P) konvex ist und die erste Größe darstellt;
    wobei der Schritt des Lösens des weiteren Problems einer optimalen Steuerung auf dem Pontryagin-Minimalprinzip und auf der Minimierung einer weiteren Hamilton-Funktion (H), die dem weiteren Problem einer optimalen Steuerung zugeordnet ist, in Bezug auf die erste Steuervariable (i), die zweite Steuervariable (P) und die Kostenvariable (λ) beruht.
  2. Verfahren nach Anspruch 1, wobei die erste Steuervariable (i) einen der folgenden Werte annimmt: einen ersten Wert, der einem Trennungszustand einer Kupplung (CL) des Fahrzeugs (101) zugeordnet ist; und mehrere zweite Werte, die jeweiligen auswählbaren Gängen eines Getriebes (GB) des Fahrzeugs (101) zugeordnet sind.
  3. Verfahren nach Anspruch 1 oder 2, wobei die Gruppe von Randbedingungen ferner mindestens eine Ungleichheitsrandbedingung umfasst, die durch eine Ungleichung ausdrückbar ist, deren erstes Element eine totale Ableitung der Zustandsvariable (Eb ) in Bezug auf eine unabhängige Variable (z) des Problems einer optimalen Steuerung ist.
  4. Verfahren nach Anspruch 3, wobei das zweite Element von der Zustandsvariable (Eb ) explizit unabhängig ist.
  5. Verfahren nach Anspruch 4, wobei die zweite Energiequelle einen Elektromotor (EM) umfasst und das zweite Element eine Leistung (Pb ) angibt, die dem Elektromotor (EM) zugeführt wird;
    wobei das mathematische Modell ein Motorleistungsmodell umfasst, für das das zweite Element als ein Polynom in der zweiten Steuervariable (P) modelliert ist, wobei die Koeffizienten von einer Ausgangswinkelgeschwindigkeit ωm des Elektromotors (EM) abhängen.
  6. Verfahren nach einem der vorhergehenden Ansprüche, wobei die erste Größe von der Zustandsvariable explizit unabhängig ist.
  7. Verfahren nach einem der vorhergehenden Ansprüche, wobei die Gruppe von Randbedingungen ferner eine zweite Ungleichheitsrandbedingung umfasst, die physikalische Grenzwerte des Fahrzeugs (101) ausdrückt.
  8. Verfahren nach einem der vorhergehenden Ansprüche, wobei mindestens eine der Randbedingungen der Gruppe von Randbedingungen durch die Kostenfunktion als eine Indikatorfunktion (ψ) eingebunden ist, die einen Wert unendlich oder null annimmt, wenn die eingebundene Randbedingung verletzt bzw. erfüllt wird.
  9. Verfahren nach einem der vorhergehenden Ansprüche, wobei das mathematische Modell mehrere a priori bekannte erste Parameter (Γ, v), die der Mission zugeordnet sind, umfasst,
    wobei das mathematische Modell die Bestimmung einer zweiten Größe (Pf ), die eine Augenblicksleistung zum Antreiben des Fahrzeugs (101) angibt, als eine Funktion der ersten Parameter (Γ, v), der ersten Steuervariable (i) und der zweiten Steuervariable (P) ermöglicht,
    und wobei die erste Größe, die die Energie angibt, die durch die erste Energiequelle (ICE) verbraucht wird, eine Funktion der zweiten Größe (Pf ) ist.
  10. Verfahren nach Anspruch 9, wobei die erste Energiequelle eine Kraftmaschine (ICE) umfasst, die konfiguriert ist, aus einem Kraftstoff Energie zu erzeugen; wobei die erste Größe und die zweite Größe den Kraftstoff, der durch das Fahrzeug (101) verbraucht wird, bzw. eine Augenblickskraftstoffleistung, die zum Antreiben des Fahrzeugs (101) erforderlich ist, angeben.
  11. Verfahren nach Anspruch 10, wobei das mathematische Modell Folgendes umfasst:
    • ein Kraftstoff/Leistungs-Modell, für das die zweite Größe (Pf ) als ein Polynom in einem zweiten Parameter modelliert ist, der eine Antriebsleistung (Pe,ts ), die durch die Kraftmaschine (ICE) zugeführt wird, angibt, wobei die Koeffizienten (κ0 , κ1, κ2 ) von einer Ausgangswinkelgeschwindigkeit (ωe ) der Kraftmaschine (ICE) abhängen;
    • ein Kraftmaschine/Leistungs-Modell, für das der zweite Parameter als eine Funktion der zweiten Steuervariable (P) und eines dritten Parameters, der eine Gesamtantriebsleistung (Preq ), die zum Antreiben des Fahrzeugs (101) erforderlich ist, angibt, modelliert ist; und
    • ein Antriebs/Leistungs-Modell, für das der dritte Parameter als eine Funktion eines Antriebswiderstands für das Fahrzeug (101) modelliert ist, wobei der Antriebswiderstand von den ersten Parametern (Γ, v) abhängt.
  12. Verfahren nach Anspruch 11, wobei die Gruppe von Randbedingungen ferner eine Gleichheitsrandbedingung umfasst, die durch das Antriebs/Leistungs-Modell ausdrückbar ist.
  13. Verfahren nach einem der Ansprüche 3 bis 12, das ferner den Schritt des Bestimmens eines optimalen Äquivalenzfaktors (s *), der einer optimalen Kostenvariable (λ *) entspricht, die die Hamilton-Funktion (H) in Bezug auf die Kostenvariable (λ) minimiert, umfasst,
    wobei das Bestimmen des optimalen Äquivalenzfaktors (s *) das Lösen mindestens eines Grenzwertproblems, wobei eine zu lösende Differentialgleichung dasselbe erste und zweite Element wie die erste Ungleichheitsrandbedingung aufweist und wobei eine zu erfüllende endgültige Bedingung der Endpunktrandbedingung zugeordnet wird, enthält.
  14. Verfahren nach Anspruch 13, wobei das Bestimmen des optimalen Äquivalenzfaktors (s *) ferner das Lösen mehrerer Grenzwertprobleme, die jeweiligen weiteren Abschnitten der Mission zugeordnet sind, enthält,
    wobei die Gruppe von Randbedingungen ferner eine Zustandsrandbedingung umfasst, die die Zustandsvariable (Eb ) zwischen einem unteren und einem oberen Grenzwert begrenzt; wobei die Zustandsrandbedingung für jeden der weiteren nachfolgenden Abschnitte der Mission gültig ist; wobei die Mission durch die weiteren nachfolgenden Abschnitte vollständig definiert wird.
  15. Verfahren nach Anspruch 3, das ferner den Schritt des Bestimmens eines optimalen Äquivalenzfaktors (s *), der einer optimalen Kostenvariable (λ *) entspricht, die die weitere Hamilton-Funktion (H) in Bezug auf die Kostenvariable (λ) minimiert, umfasst,
    wobei das Bestimmen des optimalen konstanten Äquivalenzfaktors (s *) das Lösen mindestens eines Grenzwertproblems, wobei eine zu lösende Differentialgleichung dasselbe erste und zweite Element wie die erste Ungleichheitsrandbedingung aufweist und wobei eine zu erfüllende endgültige Bedingung der Endpunktrandbedingung zugeordnet wird, enthält.
  16. Verfahren nach einem der vorhergehenden Ansprüche, das ferner die folgenden Schritte umfasst:
    • Erfassen eines ersten aktuellen Wertes (ξact ) der dritten Größe (ξ);
    • Bestimmen eines Rückkopplungsfehlers (eξ ) auf der Grundlage eines Vergleichs zwischen einem zweiten aktuellen Wert der Referenzübertragungslinie (ξ *) und dem ersten aktuellen Wert (ξact );
    • Anwenden eines Steuerungsgesetzes auf den Rückkopplungsfehler (eξ ), derart, dass ein Steuersignal (sc ) erhalten wird;
    • Erfassen eines dritten aktuellen Wertes (Preq,act ), der einer tatsächlichen Gesamtantriebsleistung zugeordnet ist, die zum Antreiben des Fahrzeugs (101) erforderlich ist;
    • Bestimmen einer optimalen ersten Steuervariable (ic ) und einer optimalen zweiten Steuervariable (P), die die Hamilton-Funktion (H) minimieren, wobei ein dritter Parameter, der die erforderliche Gesamtantriebsleistung (Preq ) angibt, und die Kostenvariable (λ) dem dritten aktuellen Wert (Preq,act ) bzw. dem Steuersignal (sc ) entsprechen; und
    • Verwenden der bestimmten optimalen ersten und zweiten Steuervariable (ic , P) zum Steuern des Fahrzeugs (101).
  17. Verfahren nach den Ansprüchen 15 und 16, das ferner den Schritt des Vorwärtskoppelns des optimalen konstanten Äquivalenzfaktors (s *) zum Steuersignal (sc ) umfasst.
  18. Verfahren nach einem der vorhergehenden Ansprüche, wobei die zweite Energiequelle einen Elektromotor (EM) umfasst und das Fahrzeug (101) eine Batterie (BY) umfasst, die zum Versorgen des Elektromotors (EM) mit dem Elektromotor (EM) gekoppelt ist;
    wobei der Energiebetrag in der Batterie (BY) gespeichert ist und den Ladungszustand (ξ) der Batterie (BY) definiert.
  19. System zum Steuern eines Fahrzeugs (101) auf einer Mission, wobei das Fahrzeug (101) eine erste und eine zweite Energiequelle (ICE, EM) zum Antreiben des Fahrzeugs (101) selbst umfasst;
    wobei das System eine Steuereinheit (ECU) umfasst, die programmiert ist, das Verfahren nach einem der Ansprüche 1-18 zu implementieren.
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